Triple
T3777075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PAW Patrol: The Movie |
E83332
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Ryder
Ryder is the young, tech-savvy leader of the PAW Patrol team who guides a group of rescue pups on missions to protect their community.
|
E387365
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Ryder | Statement: [PAW Patrol: The Movie, mainCharacter, Ryder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ryder Context triple: [PAW Patrol: The Movie, mainCharacter, Ryder]
-
A.
Ryder
Ryder is a modernist novel by Djuna Barnes, known for its experimental style and exploration of unconventional family and sexual relationships.
-
B.
Parker
Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
-
C.
Tucker
Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
-
D.
Arvin
Arvin is a small agricultural city in Southern California’s San Joaquin Valley, known for its farming economy and diverse rural community.
-
E.
Couper
Couper is a surname and variant spelling of Cooper, used by various individuals and families, particularly in English-speaking regions.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Ryder Triple: [PAW Patrol: The Movie, mainCharacter, Ryder]
Generated description
Ryder is the young, tech-savvy leader of the PAW Patrol team who guides a group of rescue pups on missions to protect their community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ryder Target entity description: Ryder is the young, tech-savvy leader of the PAW Patrol team who guides a group of rescue pups on missions to protect their community.
-
A.
Ryder
Ryder is a modernist novel by Djuna Barnes, known for its experimental style and exploration of unconventional family and sexual relationships.
-
B.
Parker
Parker is a common English surname borne by numerous notable individuals across fields such as politics, sports, arts, and science.
-
C.
Tucker
Tucker is a surname most notably associated with Albert W. Tucker, a Canadian-American mathematician and game theorist known for his contributions to topology and the formalization of the prisoner's dilemma.
-
D.
Arvin
Arvin is a small agricultural city in Southern California’s San Joaquin Valley, known for its farming economy and diverse rural community.
-
E.
Couper
Couper is a surname and variant spelling of Cooper, used by various individuals and families, particularly in English-speaking regions.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ad8b235e608190b5a2b1d1bfcef50b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcc5d3dbc8190b6ab118a56acd5a3 |
completed | March 8, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e534a02c8190b8dd76ed965f393f |
completed | March 14, 2026, 4:33 a.m. |
| NEDg | Description generation | batch_69b4e6b1cefc8190971e9441dc145e19 |
completed | March 14, 2026, 4:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4ea8b9d2c819088db1fdf9dc90c0c |
completed | March 14, 2026, 4:56 a.m. |
Created at: March 8, 2026, 3:36 p.m.